Control LM Studio from a terminal, start the server, check which models are loaded, and free memory by unloading models you're not using.
Create a new coding project that connects to a locally running AI model via LM Studio's JavaScript library.
Stream real-time logs from LM Studio to debug model behavior during development.
List all downloaded AI models and see which are actively loaded in memory with a single command.
Bundled with LM Studio 0.2.22+, contributors must clone the full lmstudio.js monorepo to build from source.
This is the official command-line tool for LM Studio, a desktop application that lets people run AI language models directly on their own computer. The tool is called lms and it comes bundled with LM Studio versions 0.2.22 and newer, so most users already have it without needing to install anything extra. From a terminal window, lms gives you typed commands to control what LM Studio is doing. You can check whether LM Studio is running, start or stop its local server, see which AI models you have downloaded, and see which models are currently loaded and ready to respond. Commands like lms ls list your downloaded models, while lms ps shows models that are actively in memory. You can also load or unload individual models by name, which lets you control how much of your computer's memory is in use. Beyond model management, lms also has a command to create a new coding project that connects to LM Studio through its software library, and a command to stream live logs so you can watch what LM Studio is doing in real time. Every subcommand has its own --help flag that explains its options, so you do not need to memorize syntax. The tool is written in TypeScript and is part of a larger collection of code called the lmstudio.js monorepo. It cannot be built in isolation, contributors need to clone the full monorepo and build the whole set before testing their changes. The README is brief and the project's main home for documentation is the LM Studio website rather than the repository itself.
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